RT Journal Article
SR Electronic
T1 Direct observation of the neural computations underlying a single decision
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.05.02.490321
DO 10.1101/2022.05.02.490321
A1 Natalie A Steinemann
A1 Gabriel M Stine
A1 Eric M Trautmann
A1 Ariel Zylberberg
A1 Daniel M Wolpert
A1 Michael N Shadlen
YR 2022
UL http://biorxiv.org/content/early/2022/05/04/2022.05.02.490321.1.abstract
AB Neurobiological investigations of perceptual decision-making have furnished the first glimpse of a flexible cognitive process at the level of single neurons1,2. Neurons in the parietal and prefrontal cortex3–6 are thought to represent the accumulation of noisy evidence, acquired over time, leading to a decision. Neural recordings averaged over many decisions have provided support for the deterministic rise in activity to a termination bound7. Critically, it is the unobserved stochastic component that is thought to confer variability in both choice and decision time8. Here, we elucidate this stochastic, diffusion-like signal on individual decisions by recording simultaneously from hundreds of neurons in the lateral intraparietal cortex (LIP). We show that a small subset of these neurons, previously studied singly, represent a combination of deterministic drift and stochastic diffusion—the integral of noisy evidence—during perceptual decision making, and we provide direct support for the hypothesis that this diffusion signal is the quantity responsible for the variability in choice and reaction times. Neuronal state space and decoding analyses, applied to the whole population, also identify the drift diffusion signal. However, we show that the signal relies on the subset of neurons with response fields that overlap the choice targets. This parsimonious observation would escape detection by these powerful methods, absent a clear hypothesis.Competing Interest StatementThe authors have declared no competing interest.